Column based database (also known as a columnar database) is a type of database that stores its data in tables made up of columns. Unlike traditional row-based databases, where data is stored in single rows, column based databases each store their data in multiple columns. The advantages of column-based databases are that they are more efficient when retrieving large amounts of data, can be used for sorting and searching of data more quickly, and are better suited for analyzing large data sets.
A column-based database works by storing data in columns, each column representing a single feature of the data, such as a product name or price. These columns contain multiple records, with each row in a column representing one instance of the feature. For example, a product name column might have rows containing the names of products, each in their own row. This way of storing data allows for a more efficient search of data by quickly narrowing down the search dependant on the column given.
Column-based databases are also known for their increased performance when dealing with large datasets. Compared to traditional row-based databases, column-based databases are faster and more efficient when retrieving large amounts of data. This is because with the data stored in columns, the database engine only has to scan through the columns relevant to a query rather than each row.
Many well-known database management systems provide support for column-based databases, such as Apache Hadoop, Apache Cassandra, MongoDB, and Microsoft’s Azure SQL Database. Popular open source column-based databases include Apache HBase and Apache Phoenix.
Column-based databases are a powerful tool, especially when dealing with large data sets. They are excellent for rapid searching and sorting of data, allowing for more efficient querying and retrieval of data. Column-based databases can be used for data analysis, data mining, and other large-scale data processing tasks.
